Abstract [en]

The overall objective of this research is to investigate the effectiveness of BJ-1 and CBERS remote sensing images for monitoring and modeling the spatial-temporal pattern change in Shanghai city. In this study, a scene of BJ-1 and two scenes of CBERS 01/02 images were used as the data sources. Comparing the accuracy of maximum likelihood classifier (MLC) and support vector machine (SVM) with two different kernel functions, the highest one in each temporal was chosen to analyze the typical ground objects and landscape pattern change. Gradient and direction characteristic analysis were also applied to calculate the degree and direction of urban growth. We selected some human and natural indicators from the Shanghai Statistical Yearbook to analyze the driving force of Shanghai. The results indicated that urbanization in Shanghai tended to be marginalization. And the urban growth has occurred in the NE-E and SE-S direction regions (Pudong New Area and Sanlin Area).